Sudomotor activity and heat balance with serial cooling and heating of thermosensors in the esophagus and stomach
Bibliographic record
Abstract
This study assessed heat balance parameters and characterized transient sweating responses on the forehead following graded changes in local temperature of the esophagus and stomach from ingesting water of different temperatures. Seven male participants cycled for 75‐min in a temperate environment while ingesting four 3.2 mL·kg −1 boluses of either 1.5°C, 10°C, 37°C or 50°C water, 5‐min before, and 15, 30 and 45‐min after the start of exercise at 50% VO 2max . Whole‐body sweat loss (WBSL), rectal temperature ( T re ), mean skin temperature ( T sk ) and local sweat rate on the forehead ( SR head ) were measured throughout. Evaporative heat loss from sweating ( E sk ), respiratory heat loss, dry heat losses and heat exchange with ingested water were subsequently calculated to estimate net body heat storage ( S ). Despite no differences in T re or T sk , the onset time for sudmotor activity on the forehead was significantly greater with declining fluid temperature (P<0.05), and both mean SR head throughout exercise and WBSL was significantly lower with 1.5°C compared to 50°C water ingestion (P=0.002). Values for S were significantly greater following 1.5°C water ingestion relative to 50°C (P=0.033), indicating a disproportionate reduction of thermoregulatory sweating, and therefore E sk , relative to the internal heat transfer with 1.5°C water. It is proposed that these data present evidence of independent thermoafferent processes arising from changes in local temperature of the esophagus and/or stomach. Funding for the study was provided by a NSERC discovery grant.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".